Maximal Subspace Coregulated Gene Clustering

2008 ◽  
Vol 20 (1) ◽  
pp. 83-98 ◽  
Author(s):  
Yuhai Zhao ◽  
J.X. Yu ◽  
Guoren Wang ◽  
Lei Chen ◽  
Bin Wang ◽  
...  
Keyword(s):  
Gene Clustering ◽  
Coregulated Gene

scholarly journals Gene clustering by using query-based self-organizing maps

2010 ◽  
Vol 37 (9) ◽  
pp. 6689-6694 ◽  
Author(s):  
Ray-I Chang ◽  
Chih-Chun Chu ◽  
Yu-Ying Wu ◽  
Yen-Liang Chen
Keyword(s):  
Gene Clustering ◽  
Self Organizing Maps ◽  
Self Organizing

scholarly journals Gene Clustering Based on RNAi Phenotypes of Ovary-Enriched Genes in C. elegans

2002 ◽  
Vol 12 (22) ◽  
pp. 1959-1964 ◽  
Author(s):  
Fabio Piano ◽  
Aaron J. Schetter ◽  
Diane G. Morton ◽  
Kristin C. Gunsalus ◽  
Valerie Reinke ◽  
...  
Keyword(s):  
Gene Clustering ◽  
C Elegans

Axonemal localization ofChlamydomonasPACRG, a homologue of the humanParkin-coregulated gene product

2007 ◽  
Vol 64 (11) ◽  
pp. 814-821 ◽  
Author(s):  
Kazuho Ikeda ◽  
Takashi Ikeda ◽  
Keiko Morikawa ◽  
Ritsu Kamiya
Keyword(s):  
Gene Product ◽  
Coregulated Gene

scholarly journals Using FIBexDB for In-Depth Analysis of Flax Lectin Gene Expression in Response to Fusarium oxysporum Infection

Plants ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 163
Author(s):  
Natalia Petrova ◽  
Natalia Mokshina
Keyword(s):  
Gene Expression ◽  
Fusarium Oxysporum ◽  
Essential Role ◽  
Protein Biosynthesis ◽  
Plant Immunity ◽  
Gene Clustering ◽  
Root Tips ◽  
Lectin Gene ◽  
Depth Analysis ◽  
Lectin Genes

Plant proteins with lectin domains play an essential role in plant immunity modulation, but among a plurality of lectins recruited by plants, only a few members have been functionally characterized. For the analysis of flax lectin gene expression, we used FIBexDB, which includes an efficient algorithm for flax gene expression analysis combining gene clustering and coexpression network analysis. We analyzed the lectin gene expression in various flax tissues, including root tips infected with Fusarium oxysporum. Two pools of lectin genes were revealed: downregulated and upregulated during the infection. Lectins with suppressed gene expression are associated with protein biosynthesis (Calreticulin family), cell wall biosynthesis (galactose-binding lectin family) and cytoskeleton functioning (Malectin family). Among the upregulated lectin genes were those encoding lectins from the Hevein, Nictaba, and GNA families. The main participants from each group are discussed. A list of lectin genes, the expression of which can determine the resistance of flax, is proposed, for example, the genes encoding amaranthins. We demonstrate that FIBexDB is an efficient tool both for the visualization of data, and for searching for the general patterns of lectin genes that may play an essential role in normal plant development and defense.

scholarly journals Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review

2021 ◽  
Vol 13 ◽  
Author(s):  
David Vogrinc ◽  
Katja Goričar ◽  
Vita Dolžan
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Age Of Onset ◽  
Association Studies ◽  
The Elderly ◽  
Gene Clustering ◽  
Molecular Pathways ◽  
Genome Wide Association Studies ◽  
Cellular Processes ◽  
Increased Risk

Alzheimer's disease (AD) is a complex neurodegenerative disease, affecting a significant part of the population. The majority of AD cases occur in the elderly with a typical age of onset of the disease above 65 years. AD presents a major burden for the healthcare system and since population is rapidly aging, the burden of the disease will increase in the future. However, no effective drug treatment for a full-blown disease has been developed to date. The genetic background of AD is extensively studied; numerous genome-wide association studies (GWAS) identified significant genes associated with increased risk of AD development. This review summarizes more than 100 risk loci. Many of them may serve as biomarkers of AD progression, even in the preclinical stage of the disease. Furthermore, we used GWAS data to identify key pathways of AD pathogenesis: cellular processes, metabolic processes, biological regulation, localization, transport, regulation of cellular processes, and neurological system processes. Gene clustering into molecular pathways can provide background for identification of novel molecular targets and may support the development of tailored and personalized treatment of AD.

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